Previously, in [1]} and [2]}, we have performed such an analysis of the simplest \(G\) -block, the Adaptive Bellman-Ford (ABF) algorithm, which estimates distances of nodes from a source set in a distributed manner and (unlike the classical Bellman-Ford algorithm [3]}) accommodates underestimates.
In [4]} we have analyzed without proof another special case, which
generalizes ABF by allowing non-Euclidean distance metrics, e.g., those that penalize
certain routes, and permits broadcast, where each source broadcasts a value like a diameter estimate it holds to nearest devices. More features are given Section .
